Current tools used to determine cardiovascular disease risk perform reasonably well in people living with HIV

A new study suggests that commonly-used risk algorithms are helpful tools in identifying how likely someone living with HIV is to develop cardiovascular disease.

Rosan van Zoest, PhD candidate with the Amsterdam Institute for Global Health and Development, recently presented her study which evaluated and compared four tools used to calculate a person’s risk for developing the common disease. Her study results were presented at the 20th International Workshop on Co-morbidities and Adverse Drug Reactions in HIV last week.

Algorithms are often used to determine how likely an individual is to develop a certain disease or illness based on different criteria. For cardiovascular disease factors including age, sex, blood pressure, cholesterol, family history and whether they smoke, for example are used to calculate a person’s risk.

It’s been shown in prior studies that people living with HIV have a higher risk of developing cardiovascular disease due to factors such as ongoing inflammation, activation of their immune system and HIV-related medication. Most algorithms used to calculate cardiovascular disease risk do not take into account these HIV-associated factors.

Rosan’s work, titled Predictive performance of cardiovascular disease risk equations in people living with HIV, sought to evaluate which algorithms worked best for accurately predicting cardiovascular disease risk in people living with HIV, given their pre-disposition to the disease. Using data from the nationwide Netherlands ATHENA observational HIV cohort, administered by Stichting HIV Monitoring, Rosan analyzed four widely used tools: one that was HIV-specific, and three that were developed for the general population. She also evaluated whether the algorithm used in the Dutch cardiovascular disease risk management guidelines could be improved by simply increasing a person’s risk by adding 5 years to their actual age.

All algorithms performed reasonably well, with the standard algorithm used in the Dutch guidelines performing the poorest.

Most algorithms underestimated the risk for people living with HIV, especially in those with a low predicted risk – something that could result in delayed treatment and thereby negatively impact their health. The underestimation by the Dutch algorithm slightly improved by assigning patients a higher risk equivalent of a 5-year increase in age. Despite their underestimation, using the algorithms provides a more accurate assessment than not using the tools at all.

“Though none of the algorithms perfectly predict the risk for developing cardiovascular disease in people living with HIV, they can provide guidance in the decision to start preventive treatment, with one caveat,,” said Rosan.

“if an individual living with HIV has a low risk according to the algorithm, in reality, their risk is likely higher. This means they may need to be treated sooner by their respective care providers.”

For her work, Rosan was one of four recipients of the newly established scholarships in memory of Professor David Cooper who passed away in 2018. Prof. Cooper was a prolific HIV researcher and co-founder of the workshop.